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Wei-ju Wu edited this page Sep 28, 2017 · 11 revisions

To demonstrate the general way of working with cMonkey2, here we run through a quick example. It is assumed that the source code is checked out, or the Debian package installed, and the prerequisites are all installed and in place (see Installation). The example was tested on a Linux-based system and should also run on a Mac OS X system without modifications.

Included in the source code repository is a small data set for Halobacterium salinarum, which completes in comparatively short time. We will use this data set to generate clusters and a web-based report.

On the command line, enter the following commands:

    cd <your cmonkey-python directory>
    bin/cmonkey2.sh --organism hal --rsat_base_url http://networks.systemsbiology.net/rsat example_data/hal/halo_ratios5.tsv 

The clustering application will now run with its default settings and automatically download the auxiliary data it needs from the web. Please ensure that you have a working internet connection. On our test system (Intel i7, 8 GB RAM), this data set finishes in about 1 hour.

cMonkey2 comes with a monitoring application, which automatically reads the output data and generates statistics about the run currently in progress.

    cd <your cmonkey-python directory>
    bin/cm2view.sh

The monitoring application will be started and can be viewed by opening a web browser and entering the address http://localhost:8080/.

After the run is finished, the results will be available in the directory <your cmonkey-python directory>/out path, which contains among other files contains the important result files:

  • ratios.tsv.gz - the normalized input matrix
  • cmonkey_run.db - the results of the cmonkey run, stored in sqlite3 format

See file formats for a more detailed description of the resulting file formats.